Blog Archives

Being the first to cross the finish line makes you a winner in only one phase of life. It’s what you do after you cross the line that really counts.– Ralph Boston

Does winner-take-all strategy apply outside the boundaries of a complex system? Let us put it another way. If one were to pursue a winner-take-all strategy, then does this willful strategic move not bind them to the constraints of complexity theory? Will the net gains accumulate at a pace over time far greater than the corresponding entropy that might be a by-product of such a strategy? Does natural selection exhibit a winner-take-all strategy over time and ought we then to regard that winning combination to spur our decisions around crafting such strategies? Are we fated in the long run to arrive at a world where there will be a very few winners in all niches and what would that mean? How does that surmise with our good intentions of creating equal opportunities and a fair distribution of access to resources to a wider swath of the population? In other words, is a winner take all a deterministic fact and does all our trivial actions to counter that constitute love’s labor lost?

Natural selection is a mechanism for evolution. It explains how populations or species evolve or modify over time in such a manner that it becomes better suited to their environments. Recall the discussion on managing scale in the earlier chapter where we discussed briefly about aligning internal complexity to external complexity. Natural selection is how it plays out at a biological level. Essentially natural selection posits that living organisms have inherited traits that help them to survive and procreate. These organisms will largely leave more offspring than their peers since the presumption is that these organisms will carry key traits that will survive the vagaries of external complexity and environment (predators, resource scarcity, climate change, etc.) Since these traits are passed on to the next generate, these traits will become more common until such time that the traits are dominant over generations, if the environment has not been punctuated with massive changes. These organisms with these dominant traits will have adapted to their environment. Natural selection does not necessarily suggest that what is good for one is good for the collective species.

An example that was shared by Robert Frank in his book “The Darwin Economy” was the case of large antlers of the bull elk. These antlers developed as an instrument for attracting mates rather than warding off predators. Big antlers would suggest a greater likelihood of the bull elk to marginalize the elks with smaller antlers. Over time, the bull elks with small antlers would die off since they would not be able to produce offspring and pass their traits. Thus, the bull elks would largely comprise of those elks with large antlers. However, the flip side is that large antlers compromise mobility and thus are more likely to be attacked by predators. Although the individual elk with large antler might succeed to stay around over time, it is also true that the compromised mobility associated with large antlers would overall hurt the propagation of the species as a collective group. We will return to this very important concept later. The interests of individual animals were often profoundly in conflict with the broader interests of their own species. Corresponding to the development of the natural selection mechanism is the introduction of the concept of the “survival of the fittest” which was introduced by Herbert Spencer. One often uses natural selection and survival of the fittest interchangeable and that is plain wrong. Natural selection never claims that the species that will emerge is the strongest, the fastest, the largest, etc.: it simply claims that the species will be the fittest, namely it will evolve in a manner best suited for the environment in which it resides. Put it another way: survival of the most sympathetic is perhaps more applicable. Organisms that are more sympathetic and caring and work in harmony with the exigencies of an environment that is largely outside of their control would likely succeed and thrive.

We will digress into the world of business. A common conception that is widely discussed is that businesses must position toward a winner-take-all strategy – especially, in industries that have very high entry costs. Once these businesses entrench themselves in the space, the next immediate initiative would be to literally launch a full-frontal assault involving huge investments to capture the mind and the wallet of the customer. Peter Thiel says – Competition is for losers. If you want to create and capture lasting value, look to build a monopoly.” Once that is built, it would be hard to displace!

Scaling the organization intentionally is key to long-term success. There are a number of factors that contribute toward developing scale and thus establishing a strong footing in the particular markets. We are listing some of the key factors below:

Barriers to entry: Some organizations have natural cost prohibitive barriers to entry like utility companies or automobile plants. They require large investments. On the other hand, organizations can themselves influence and erect huge barriers to entry even though the barriers did not exist. Organizations would massively invest in infrastructure, distribution, customer acquisition and retention, brand and public relations. Organizations that are able to rapidly do this at a massive scale would be the ones that is expected to exercise their leverage over a big consumption base well into the future.

Multi-sided platform impacts: The value of information across multiple subsystems: company, supplier, customer, government increases disproportionately as it expands. We had earlier noted that if cities expand by 100%, then there is increasing innovating and goods that generate 115% -the concept of super-linear scaling. As more nodes are introduced into the system and a better infrastructure is created to support communication and exchange between the nodes, the more entrenched the business becomes. And interestingly, the business grows at a sub-linear scale – namely, it consumes less and less resources in proportion to its growth. Hence, we see the large unicorn valuation among companies where investors and market makers place calculated bets on investments of colossal magnitudes. The magnitude of such investments is relatively a recent event, and this is largely driven by the advances in technology that connect all stakeholders.

Investment in learning: To manage scale is to also be selective of information that a system receives and how the information is processed internally. In addition, how is this information relayed to the external system or environment. This requires massive investment in areas like machine learning, artificial intelligence, big data, enabling increased computational power, development of new learning algorithms, etc. This means that organizations have to align infrastructure and capability while also working with external environments through public relations, lobbying groups and policymakers to chaperone a comprehensive and a very complex hard-to-replicate learning organism.

Investment in brand: Brand personifies the value attributes of an organization. One connects brand to customer experience and perception of the organization’s product. To manage scale and grow, organizations must invest in brand: to capture increased mindshare of the consumer. In complexity science terms, the internal systems are shaped to emit powerful signals to the external environment and urge a response. Brand and learning work together to allow a harmonic growth of an internal system in the context of its immediate environment.

However, one must revert to the science of complexity to understand the long-term challenges of a winner-take-all mechanism. We have already seen the example that what is good for the individual bull-elk might not be the best for the species in the long-term. We see that super-linear scaling systems also emits significant negative by-products. Thus, the question that we need to ask is whether the organizations are paradoxically cultivating their own seeds of destruction in their ambitions of pursuing scale and market entrenchment.

When you seed another social network into an ecosystem, you are, for the lack of a better word, embracing the tenets of a standing ovation model. The standing ovation model has become, as of late, the fundamental rubric upon which several key principles associated with content, virality, emulation, cognitive psychology, location principles, social status and behavioral impulse coalesce together in various mixes to produce what would be the diffusion of the social network principles as it ripples through the population it contacts. Please keep in mind that this model provides the highest level perspective that fields the trajectory of the social network dynamics. There are however a number of other models that are more tactical and borrowed from the fields of epidemiology and growth economics that will address important elements like the tipping points that generally play a large role in essentially creating that critical mass of crowdswell, which once attained is difficult to reverse, unless of course there are legislative and technology reversals that may defeat the dynamics.

So I will focus, in this post, the importance of standing ovation model. The basic SOP (Standing Ovation problem) can be simply stated as: A lecture or content display in an audience ends and the audience starts to applaud. The applause builds and tentatively, a few audience may members may or may not decide to stand. This could be abstracted in our world as an audience that is a passive user versus an active user in the ecosystem. The question that emerges is whether a standing ovation ensues or does the enthusiasm fizzle. SOP problems were first studied by Schelling.

In the simplest form of the model, when a performance or content consumption ends, an audience member must decide whether or not to stand. Now if the decision to stand is made without any consideration of the dynamics of the other people in the audience, then there is no problem per se and the SOP model does not come into play. However, if the random person is on the fence or is reluctant or may not have enjoyed the content … would the behavioral and location dynamics of the other participants in the audience influence him enough to stand even against his better judgment. The latter case is an example of information cascade or what is often called the “following the herd” mentality which essentially means that the individuals abnegates his position in favor of the collective judgment of the people around him. So this model and its application to social networks is best explained by looking at the following elements:

1. Group Response: If you are part of a group and you have your set of judgments governing your decision to stand up, then are you willing to reserve those judgments to be part of group behavior. At what point is a person willing to seed doubt and play along with a larger response. This has important implications. For example, if you are in an audience and a member of a group that you know well, and a certain threshold quantity in the group responds favorably to the content, there may be some likelihood that you would follow along. On the other hand, if you are an individual in an audience, albeit not connected to a group, there is still some chance of you to follow along as long as it meets some threshold for example – if I can see about people stand, I will follow along. In a known group which may constitute you being a participant among five people, even if 3 people stand, you may stand up even though it does not meet your random 10 people formula. This has important implications in cohorts, building groups, providing tools and computational agents in social networks and dynamics to incline a passive consumer to an active consumer.

2. Visibility to the Group: Location is an important piece of the SOP. Imagine a theater. If you are the first one in the center of all rows, you will, unless you turn back, not be cognizant of people’s reactions. Thus, your response to the content will be preliminarily fed by the intensity of your reaction to the content. On the other hand, if you are seated behind, you will have a broader perspective and you may respond to the dynamics of how the others respond to the content. What does this mean in social dynamics and introducing more active participation? Simply that you have to again provide the underlying mechanisms that allow people to respond at a temporal level ( a short time frame) to how a threshold mass of people have responded. Affording that one person visibility that would follow up with a desired response would create the information cascade that would culminate in a large standing ovation.

3. Beachhead Response: An audience will have bias. That is another presumption in the model. They will carry certain judgments prior to a show – one of which is that the people in front who have bought the expensive seats are influential and have “celebrity” status. Now depending on the weight of this bias, a random person, in spite a positive audience response, may not respond positively if the front rows do not respond positively. Thus, he is heavily inclined to discounting the general audience threshold toward a threshold associated with a select group that could result in different behavior. However, it is also possible that if the beachhead responds positively and not the audience, the random person may react positively despite the general threshold dynamics. So the point being that designing and developing products in a social environment have to be able to measure such biases, see responses and then introduce computational agents to create fuller participation.

Thus, the SOP is the fundamental crux around which a product design has to be considered. In that, to the extent possible, you bring in a person who belongs to a group, has the spatial visibility, and responds accordingly would thus make for an enduring response to content. Of course, the content is a critical component as well for poor content, regardless of all ovation agents introduced, may not trigger a desired response. So content is as much an important pillar as is the placing of the random person with their thresholds of reaction. So build the content, design the audience, and design the placement of the random person in order that all three coalesce to make an active participant result out of a passive audience.

IN THE end, Microsoft fooled everyone. The replacement for its widely disparaged Windows 8 operating system turned out to be not Windows 9, as expected, but Windows 10. No explanation, other than marketing waffle, was given as to why the company should skip a release number.

IF YOU want something done, the saying goes, give it to a busy person. It is an odd way to guarantee hitting deadlines. But a paper recently published in the Journal of Consumer Research suggests it may, in fact, be true—as long as the busy person conceptualises the deadline in the right way.

EVER since the “paperless office” was first mooted in a Business Week article back in 1975, its estimated time of arrival has always been ten years away. And so it remains. The amount of paper used in homes and offices has declined slightly over the past decade.

WHEN the autonomous cars in Isaac Asimov's 1953 short story “Sally” encourage a robotic bus to dole out some rough justice to an unscrupulous businessman, the reader is to believe that the bus has contravened Asimov's first law of robotics, which states that “a robot may not injure a human being or, through inaction, allow a human bein...